Adaptive Gibbs samplers and related MCMC methods
Łatuszyński, Krzysztof, Roberts, Gareth O. and Rosenthal, Jeffrey S. (Jeffrey Seth) (2011) Adaptive Gibbs samplers and related MCMC methods. Working Paper. Coventry: University of Warwick. Centre for Research in Statistical Methodology. (Working papers).
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Official URL: http://www2.warwick.ac.uk/fac/sci/statistics/crism...
We consider various versions of adaptive Gibbs and Metropolis-
within-Gibbs samplers, which update their selection probabilities (and perhaps also their proposal distributions) on the
y during a run, by learning
as they go in an attempt to optimise the algorithm.We present a cautionary
example of how even a simple-seeming adaptive Gibbs sampler may fail to
converge.We then present various positive results guaranteeing convergence
of adaptive Gibbs samplers under certain conditions.
|Item Type:||Working or Discussion Paper (Working Paper)|
|Subjects:||Q Science > QA Mathematics|
|Divisions:||Faculty of Science > Statistics|
|Library of Congress Subject Headings (LCSH):||Monte Carlo method, Markov processes, Sampling (Statistics)|
|Series Name:||Working papers|
|Publisher:||University of Warwick. Centre for Research in Statistical Methodology|
|Place of Publication:||Coventry|
|Status:||Not Peer Reviewed|
|Access rights to Published version:||Open Access|
|Funder:||Natural Sciences and Engineering Research Council of Canada (NSERC), University of Warwick. Centre for Research in Statistical Methodology, Engineering and Physical Sciences Research Council (EPSRC)|
 C. Andrieu and E. Moulines (2006): On the ergodicity properties of some
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